Wireless device location information is necessary for the operation of cellular telecommunications services. This location information enables calls to be established from these devices and calls to be delivered to these devices wherever they may be, even if they are outside a user's home network. Location information is also used to effect hand-offs among cell sites within the cellular network. The term “cellular” refers to a network of individual “cells” or “cell site” areas covered by radio transceiver systems that control communications within that cell site. Each cell site provides a limited range and radius of radio coverage to wireless devices across a defined and limited geographic area. Cellular radio transceivers within a cell site serve wireless devices within the radius of that particular cell site. Multiple cellular radio transceiver systems (or cell sites) are controlled by a centralized computer switching system. This switching system, known as the Mobile Switching Center (MSC), has information about which cell sites currently provide radio communications services to particular wireless devices. Hence, a particular MSC also has a defined and limited geographic coverage area which is defined as the aggregate of all of the cell site geographic areas of the cells that it controls. Cell site areas may also be subdivided into smaller “cell sectors.” This subdivision of cell sites into sectors enables more efficient use of radio spectrum which, in turn, enables cellular telecommunications service to be provided to more wireless devices within the original cell site area. The defined geographic areas of MSCs, cell sites and cell site sectors are location areas for which the MSC controls voice and data communications to and from individual wireless devices. Therefore, the MSC maintains current information about which wireless devices are served by which cell sites and cell site sectors. The geographic area of an MSC may be quite large, hundreds or thousands of square miles. The geographic area of a cell site typically covers a few square miles or less (especially in urban areas) and the geographic area of a cell site sector is about one-third that of a cell site. However, for a variety of vital wireless communications services, as well as the ability to enable additional value-added services, much more precise positioning information of wireless devices may be required.
Precise wireless device location information derived by a wireless network has become increasingly important in recent years. So-called “Location Based Services” (LBS) were originally required to locate wireless telecommunications network users in emergency situations. An individual may use a wireless device to call for emergency assistance. The wireless telecommunications network automatically derives the location of the mobile device and uses that location information to inform emergency services personnel of the whereabouts of the caller. This scenario is in contrast to wireline telephones used to call for emergency assistance as a wireline telephone used to make an emergency call is always associated with a static geographic location or address. Wireless or mobile devices, on the other hand, can be in any geographic location and can be moved from place to place. Hence, technologies required to precisely, automatically and dynamically locate a moveable wireless device in real-time were implemented and deployed by the wireless network operators. These technologies have proven highly useful and valuable enabling emergency services personnel to locate individuals in emergency situations.
In the late 1990s, both as a result of government regulations requiring location-based technologies for emergency services and the creation of technology standards and specifications to provide location information for wireless devices, many other value-added applications and services were created to make use of wireless location information. These applications and services are provided by both the wireless network operators themselves as well as by third-party application and services providers. Principally among these are two categories of applications and services: 1) mapping and navigation services and 2) so-called “concierge” services. Mapping and navigation services provide wireless device users the ability to find points of interest, proximity to those points of interest and real-time directions to get to those points of interest. Concierge services provide a variety of information to a user based on their current and real-time location or a location input by the user. Among these services are listings of closest locations of points of interest such as hotels, restaurants, transportation and entertainment venues. Many of these services, including emergency services, require precise location information which may only be obtained if the wireless network employs additional sophisticated location technologies. Chief among these technologies is the satellite-based Global Positioning System (GPS). Use of GPS for precise location services requires GPS technology to be incorporated into wireless devices as well as within the wireless network. However, to provide precise location information about wireless devices where GPS is not used, smart antenna technology may be employed. Smart antenna technology requires special equipment to be deployed at each cell site. This equipment analyzes multiple radio transceiver signals coming from wireless devices. Mathematical algorithms are used to determine the position of the wireless device based on the time difference of arrival (TDOA) or the angle of arrival (AOA) of the radio signals, or both. GPS is typically more accurate for precise positioning of a wireless device; however, both GPS and smart antenna technology have the potential to provide Latitude and Longitude coordinates for a wireless device from a few feet to a few hundred yards. Therefore, wireless networks currently maintain the ability to provide positioning information for particular wireless devices for areas as wide as an MSC serving area, to smaller cell site areas, to smaller cell site sector areas and many provide positioning information to a high degree of resolution by providing more precise latitudinal and longitudinal coordinates.
In a seemingly unrelated area of technology, distinct from wireless device location technology, there exists a myriad of current methods that provide for authentication, verification and validation of user activity as well as for user identity. These technologies are used to ensure that an individual is the actual person claimed for the benefit of the activity or transaction. Today, many employed technologies have greatly reduced fraudulent transactions, but instances of fraudulent activity still occur. These technologies are employed, for instance, when an individual engages in some transaction that requires some degree of security. An automated financial transaction is a common example of a secure transaction requiring mechanisms to authenticate, verify and validate the identity of the individual attempting to perform the transactional activity. Primary examples of such transactions include accessing automated teller machines (ATMs) to obtain money or to perform some other banking function and the use of credit or debit cards at a point of sale (POS) to make a purchase. Even electronic commerce-based transactions (e-commerce) and online banking, where an individual enters financial information into a website form on a personal computer to make a purchase or to perform a financial activity, require some form of authentication, verification and validation. Typical means to authenticate individuals attempting a secure transaction include use of personal identification numbers (PINs) or some other type of information that is assumed to be known only by an authorized user involved in the transaction. Other means of documentation may also be used to verify identity, such as a driver's license or other form of photo identification. Even the use of biometric devices, such as fingerprint scanners, may be used to authenticate an individual attempting to perform a secure transaction. However, even with these and many other technologies employed, fraudulent activity still occurs and identity theft and misrepresentation remains a problem.
In addition, many existing fraud detection and prevention technologies can and do provide a false positive indication of fraudulent activity. Besides the fraud detection and prevention mechanisms already mentioned, other technologies may be employed such as behavioral profiling which is used to detect anomalous behavior. These technologies employ intelligent algorithms to analyze past user behavior when a user attempts to engage in a some activity or transaction that is similar to a previous activity or transaction. If the individual's behavior when engaging in a secure activity is not consistent with that individual's past behavior, a likelihood of fraudulent activity may be deduced. Common examples of this situation are when an individual uses a credit card to purchase some product or service in a foreign country where they have never previously performed a similar transaction. Or, the amount of a particular transaction is significantly different from any previous transaction. This behavior may appear anomalous to a fraud detection system and the activity or transaction being performed may be terminated before any potential fraud is perpetrated. If this is in fact a false positive indication and the individual is actually an authorized user, the user suffers the consequences of a failed transaction and the service provider is perceived to have provided a poor quality of service.
Also, debit or credit cards may be stolen, PINs may become compromised and information meant to be held only by authorized users may become known to others. The reality is that other means to perform authentication, verification and validation of authorized users to assist in an authentication process continues to have relevance for transactions where fraudulent activity remains a problem. In many of the examples provided, the authentication technology employed involves some user interaction with a computerized device that is typically connected to a data communications network. The data communications network may maintain location information representing the actual geographic place where a secure transaction or some activity by an individual is occurring. This is true in the case of ATM transactions, automated POS transactions, personal computer-based transactions and others.
To provide authentication or additional authentication confidence where individuals attempt to perform some automated secure transaction or activity, the location of the secure transaction or activity may be ascertained from the network that is being accessed via the transactional application. As the use of wireless devices has become ubiquitous, it may be reasonably assumed that individuals carrying such a device would have the device with them while attempting to engage in a secure transaction or activity. In this case, comparing the location of the wireless device obtained from the wireless network with the location where the user of the wireless device is attempting to engage in a secure transaction or activity, may provide resultant information that may be used to authenticate, verify or validate that the user is in fact who he claims to be. Moreover, if the result from such a geographic location comparison reveals that the wireless device is in some location other than where the secure transaction or activity is taking place, it may be reasonably assumed that the user is not who he claims to be. Depending on the resolution of the geographic locations obtained from both the wireless network and some other data communications network where an activity or transaction occurs, varying degrees of confidence may be ascertained as to the authenticity of that activity or transaction. False positive indications of anomalous behavior may also be avoided. An example of this may be when an individual performs an activity or transaction and that individual is in a significantly different location than previously visited but the individual is in fact who he claims to be.
Besides the mitigation of fraudulent activity, knowledge of the location of one or more individuals for use in value-added applications may be useful. Such knowledge of both the location of a wireless device as well as the location of the wireless device user performing some automated activity or transaction may provide utility regardless of whether that activity requires security. Many value-added applications may benefit from such comparative geographic location information such as social networking applications or multi-player online gaming applications where it may be desirable for an individual to know the proximity of friends with which they wish to communicate. These friends may be engaging in some automated activity where the application is connected to a computer network where location information may be ascertained or they may be wireless device users themselves where the location of their wireless devices may be obtained from the same or another wireless network.
Many automated fraud detection and prevention systems may assign a value or range of values indicating the likelihood of fraudulent activity. These assigned values may depend on the security level required for a particular transaction or activity as well as the methods used to indicate fraud. Such a mechanism may also be employed when the comparison of two or more locations, at least one being the location of a wireless device obtained from a wireless network, results in the ability to ascertain varying degrees of confidence based on the proximity of the two geographic locations being compared.
To successfully compare two or more geographic locations, one of which being the location of a wireless device obtained from a wireless network, one or more unique wireless device identification values is required to appropriately associate the geographic locations with each other. Many unique wireless identification values are available for use. Among those that may be appropriate is the Mobile Directory Number (MDN) which is defined as the dialable directory number of the wireless device. The MDN is a uniquely provisioned value for each cellular-based telecommunications user. Other unique wireless device identification values that may be used include the serial number of the wireless device or the unique subscription identifier that may be found, for example, on a smart card used within a wireless device. Depending on the wireless technology and device used, the unique wireless device identifier appropriate for the device may be used to facilitate the geographic location comparison. Besides cellular telecommunications technology, other wireless devices from which location information may be derived and obtained from a data communications network may be supported. These wireless devices may include any type of Global Positioning System (GPS) device, Mobile Internet Device (MID), Radio Frequency Identification (RFID) device, Near Field Communications (NFC) device (such as Bluetooth or infrared-based devices) or any wireless device.
When performing a comparison among two or more particular geographic locations, the location information for a wireless device may be provided in a variety of formats. Mobile Switching Center (MSC) identification, cell site identification, cell sector identification and even Latitude and Longitude or other coordinates may be provided as well as a geographic area or place name mapped to these identifiers and coordinates. For location information obtained from other types of data communications networks, the format may be in the form of a physical geographic address (e.g., street number, street name, city, state, province, country, postal code, ZIP code, etc.), a physical data communications address (e.g., an Internet Protocol geographic address of the form XX.XX.XX.XX), a logical or virtual place or data communications address (e.g., a post office box or a uniform resource locator or URL address), some representation of an address (e.g., an alias name or label identifying an address), a geographic place name (e.g., “Central Park”), mapping coordinates (e.g., Latitude and Longitude or other projection coordinates) or a mapping identifier in some customized format. A system and method that compares such geographic locations with each other that may be obtained in any of these formats requires a mechanism to convert these different location formats into a common format type enabling comparison. A method or mechanism to derive proximity among the geographic locations that are compared may also be beneficial.
There is a need for additional and improved systems and methods to assist, for example, with fraud management systems and identity recognition and authentication. These systems are employed in a variety of industries, including banking and finance, commerce, security and others. In many cases, existing technologies employ detection methods as opposed to prevention methods. That is, many technologies and systems currently in place attempt to detect some fraudulent activity after it has occurred, and then prevent similar fraudulent activity in the future based on this detection. These methods are not optimal as fraudulent activity may be successful in at least one instance prior to detection and subsequent prevention. Prevention of fraudulent activity the first time an attempt is made is certainly preferable, as well as reducing incidences of false positive indications of fraud. No fraud detection and prevention system is perfect and there is always a need to employ additional technologies to further reduce fraud and identity theft, thereby reducing the economic impact of such undesired activity. Although many fraud detection and prevention technologies exist today, these technologies are constantly evolving and new fraud prevention technologies can always be employed to maintain additional security and lessen the economic impact. In addition, a system that can provide proximity information among one or more locations has implications beyond fraud prevention. Proximity information can add great value to other technologies such as social communications among groups and individuals. Any technology that enables such social communications may be enhanced by allowing users of that technology to know the proximity of other users.